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» Resampling methods for input modeling
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UAI
2008
13 years 8 months ago
Small Sample Inference for Generalization Error in Classification Using the CUD Bound
Confidence measures for the generalization error are crucial when small training samples are used to construct classifiers. A common approach is to estimate the generalization err...
Eric Laber, Susan Murphy
BMCBI
2007
134views more  BMCBI 2007»
13 years 7 months ago
A framework for significance analysis of gene expression data using dimension reduction methods
Background: The most popular methods for significance analysis on microarray data are well suited to find genes differentially expressed across predefined categories. However, ide...
Lars Halvor Gidskehaug, Endre Anderssen, Arnar Fla...
EDUTAINMENT
2008
Springer
13 years 9 months ago
Efficient Method for Point-Based Rendering on GPUs
Abstract. We describe methods for high-performance and high-quality rendering of point models, including advanced shading, anti-aliasing, and transparency. we keep the rendering qu...
La-mei Yan, You-wei Yuan
CDC
2010
IEEE
144views Control Systems» more  CDC 2010»
13 years 2 months ago
Semiparametric identification of Hammerstein systems using input reconstruction and a single harmonic input
We present a two-step method for identifying SISO Hammerstein systems. First, using a persistent input with retrospective cost optimization, we estimate a parametric model of the l...
Anthony M. D'Amato, Kenny S. Mitchell, Bruno Ot&aa...
WSC
2004
13 years 8 months ago
Input Modeling Using Quantile Statistical Methods
This paper applies quantile data analysis to input modeling in simulation. We introduce the use of QIQ plots to identify suitable distributions fitting the data and comparison dis...
Abhishek Gupta, Emanuel Parzen